Abstract
A feed-forward neural network trained using backpropagation was used to discriminate between b and light quark jets in e + e − → Z 0 → q q events. The information presented to the network consisted of 25 jet shape variables. Th network successfully identified b jets in two- and three-jet events modeled using a detector simulation. The jet identification efficiency for two-jet events was 61% and the probability to call a light quark jet a b jet equal to 20%.
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